Evaluation of geological hazard susceptibility based on the multi-kernel density information method

The increasing occurrence of geological hazards along roadway infrastructures presents a significant concern. Evaluating geological hazard susceptibility along roads is a critical aspect of geological disaster emergency response and rescue efforts. Accurate evaluation outcomes are essential as they play a crucial role in mitigating potential financial losses. However, previous studies on geological hazard susceptibility treated all samples as independent entities, overlooking their spatial interactions. This study introduces a novel geological hazard susceptibility assessment model termed the multi-kernel density information (MKDI) method. The MKDI method integrates information value with kernel density estimation, effectively capturing the spatial dependencies among samples. Furthermore, distinct bandwidths are prescribed for various scales of disasters to facilitate multi-kernel density estimation for geological hazards. The integration of the information method enables the development of a comprehensive geological hazard susceptibility map, capturing the spatial complexities of geological hazard distribution. To validate the effectiveness of the proposed method, the study area selected for investigation was the G219 National Highway within Zayu County. Various factors were considered for geological hazard susceptibility mapping, including slope, aspect, profile and plan curvature, river and road linear densities, peak ground acceleration, seismic response spectrum characteristics, lithology, elevation, rainfall, and landform. The results show that the MKDI model outperformed previous methods, achieving an AUC value of 0.99. The derived susceptibility map is expected to offer a scientific basis for urban planning, construction, and geological hazard risk management in the study area.

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Publication Details

Journal
Scientific Reports
Published
2025-03-06
DOI
https://doi.org/10.1038/s41598-025-91713-6
Citations
10
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
24.22
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article

Evaluation of geological hazard susceptibility based on the multi-kernel density information method

Yang Li, Yutian Lei, Jiale Chen, Bo Chen
10 citations
Scientific Reports
Landslides and related hazards
24.22
article

Evaluation of geological hazard susceptibility based on the multi-kernel density information method

Yang Li, Yutian Lei, Jiale Chen, Bo Chen
article en
10 citations

Abstract

The increasing occurrence of geological hazards along roadway infrastructures presents a significant concern. Evaluating geological hazard susceptibility along roads is a critical aspect of geological disaster emergency response and rescue efforts. Accurate evaluation outcomes are essential as they play a crucial role in mitigating potential financial losses. However, previous studies on geological hazard susceptibility treated all samples as independent entities, overlooking their spatial interactions. This study introduces a novel geological hazard susceptibility assessment model termed the multi-kernel density information (MKDI) method. The MKDI method integrates information value with kernel density estimation, effectively capturing the spatial dependencies among samples. Furthermore, distinct bandwidths are prescribed for various scales of disasters to facilitate multi-kernel density estimation for geological hazards. The integration of the information method enables the development of a comprehensive geological hazard susceptibility map, capturing the spatial complexities of geological hazard distribution. To validate the effectiveness of the proposed method, the study area selected for investigation was the G219 National Highway within Zayu County. Various factors were considered for geological hazard susceptibility mapping, including slope, aspect, profile and plan curvature, river and road linear densities, peak ground acceleration, seismic response spectrum characteristics, lithology, elevation, rainfall, and landform. The results show that the MKDI model outperformed previous methods, achieving an AUC value of 0.99. The derived susceptibility map is expected to offer a scientific basis for urban planning, construction, and geological hazard risk management in the study area.

Scientific ReportsVol. 15(1)
China University of Geosciences (CN), Energy Research Institute (CN), China Southern Power Grid (China) (CN)
Climate action
Openalex Percentile: Top 1%
Landslides and related hazards
24.22
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